DEEP LEARNING TO PREDICT DEGREE OF INTERSTITIAL FIBROSIS AND TUBULAR ATROPHY FROM KIDNEY ULTRASOUND IMAGES – AN ARTIFICIAL INTELLIGENCE APPROACH

ABSTRACTBackgroundInterstitial fibrosis and tubular atrophy (IFTA) is a strong predictor of decline in kidney function. Non-invasive test to assess IFTA is not available.MethodsWe trained, validated and tested a deep learning (DL) system to classify IFTA grade from 6,135 ultrasound images obtained from 352 patients who underwent kidney biopsy. Of 6,135 ultrasound images, 5,523 were used for training (n = 5,122) and validation (n = 401) and 612 to test the accuracy of the DL system. IFTA grade scored by nephropathologist on trichrome stained kidney biopsy slide was used as reference standard.ResultsThere were 159 patients (2,701 ultrasound images), 74 patients (1,239 ultrasound images), 41 patients (701 ultrasound images) and 78 patients (1,494 ultrasound images) with IFTA grades 1, 2, 3 and 4, respectively. The deep-learning classification system used masked images based on a 91% accurate kidney segmentation routine. The performance matrices for the deep learning classifier algorithm in the validation set showed excellent precision (90%), recall (76%), accuracy (84%) and F1-score (80%). In the independent test set also, performance matrices showed excellent precision (90%), recall (80%), accuracy (87%) and F1-score of (84%). Accuracy was highest for IFTA grade 1 (98%) and IFTA grade 4 (82%).ConclusionA DL system can accurately predict IFTA from kidney ultrasound image.</jats:sec

T-DM1, a novel antibody-drug conjugate, is highly effective against uterine and ovarian carcinosarcomas overexpressing HER2

INTRODUCTION: Ovarian and uterine carcinosarcoma (CS) are characterized by their aggressive clinical behavior and poor prognosis. We evaluated the efficacy of trastuzumab-emtansine (T-DM1), against primary HER2 positive and HER2 negative CS cell lines in vitro and in vivo. METHODS: Eight primary CS cell lines were evaluated for HER2 amplification and protein expression by FISH, immunohistochemistry, flow cytometry and qRT-PCR. Sensitivity to T-DM1-induced antibody-dependent-cell-mediated-cytotoxicity (ADCC) was evaluated in 4-hr-chromium-release-assays. T-DM1 cytostatic and apoptotic activities were evaluated using flow cytometry based proliferation assays. In vivo activity of T-DM1 was also evaluated. RESULTS: HER2 protein overexpression and gene amplification were detected in 25% (2/8) of the primary CS cell lines. T-DM1 and T were similarly effective in inducing strong ADCC against CS overexpressing HER2 at 3+ levels. In contrast, T-DM1 was dramatically more effective than T in inhibiting cell proliferation (P<0.0001) and in inducing G2/M phase cell cycle arrest in the HER2 expressing cell lines (shift of G2/M: mean ± SEM from 14.87 ± 1.23% to 66.57 ± 4.56%, P<0.0001). Importantly, T-DM1 was highly active at reducing tumor formation in vivo in CS xenografts overexpressing HER2 (P=0.0001 and P<0.0001 compared to T and vehicle respectively) with a significantly longer survival when compared to T and vehicle mice (P=0.008 and P=0.0001 respectively). CONCLUSION: T-DM1 may represent a novel treatment option for the subset of HER2 positive CS patients with disease refractory to chemotherapy